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NeuroImage: Clinical 4 (2014) 488–499

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Contents lists available at ScienceDirect

NeuroImage: Clinical

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / y n i c l

ltered resting-state functional connectivity in patients with

hronic bilateral vestibular failure

artin G ̈ottlich, Nico M. Jandl, Jann F. Wojak, Andreas Sprenger, Janina von der Gablentz, Thomas F. M ̈unte, lrike M. Kr ̈amer, Christoph Helmchen *

epartment of Neurology, University of L übeck, Ratzeburger Allee 160, L übeck 23538, Germany

r t i c l e i n f o

rticle history:

eceived 15 January 2014

eceived in revised form 26 February 2014

ccepted 9 March 2014

eywords:

esting-state fMRI

unctional connectivity

egree

ilateral vestibular failure

estibulo-ocular reflex

a b s t r a c t

Patients with bilateral vestibular failure (BVF) suffer from gait unsteadiness, oscillopsia and impaired spatial

orientation. Brain imaging studies applying caloric irrigation to patients with BVF have shown altered neural

activity of cortical visual–vestibular interaction: decreased bilateral neural activity in the posterior insula and

parietal operculum and decreased deactivations in the visual cortex. It is unknown how this affects functional

connectivity in the resting brain and how changes in connectivity are related to vestibular impairment.

We applied a novel data driven approach based on graph theory to investigate altered whole-brain resting-

state functional connectivity in BVF patients ( n = 22) compared to age- and gender-matched healthy controls ( n = 25) using resting-state fMRI. Changes in functional connectivity were related to subjective (vestibular scores) and objective functional parameters of vestibular impairment, specifically, the adaptive changes

during active (self-guided) and passive (investigator driven) head impulse test (HIT) which reflects the

integrity of the vestibulo-ocular reflex (VOR).

BVF patients showed lower bilateral connectivity in the posterior insula and parietal operculum but higher

connectivity in the posterior cerebellum compared to controls. Seed-based analysis revealed stronger con-

nectivity from the right posterior insula to the precuneus, anterior insula, anterior cingulate cortex and the

middle frontal gyrus. Excitingly, functional connectivity in the supramarginal gyrus (SMG) of the inferior

parietal lobe and posterior cerebellum correlated with the increase of VOR gain during active as compared

to passive HIT, i.e., the larger the adaptive VOR changes the larger was the increase in regional functional

connectivity.

Using whole brain resting-state connectivity analysis in BVF patients we show that enduring bilateral deficient

or missing vestibular input leads to changes in resting-state connectivity of the brain. These changes in the

resting brain are robust and task-independent as they were found in the absence of sensory stimulation

and without a region-related a priori hypothesis. Therefore they may indicate a fundamental disease-related

change in the resting brain. They may account for the patients’ persistent deficits in visuo-spatial attention,

spatial orientation and unsteadiness. The relation of increasing connectivity in the inferior parietal lobe,

specifically SMG, to improvement of VOR during active head movements reflects cortical plasticity in BVF

and may play a clinical role in vestibular rehabilitation. c © 2014 The Authors. Published by Elsevier Inc.

This is an open access article under the CC BY-NC-ND license

( http: // creativecommons.org / licenses / by-nc-nd / 3.0 / ).

. Introduction

Bilateral vestibular failure (BVF) is a severe chronic disorder of the

abyrinth or the eighth cranial nerve characterized by unsteadiness of

ait and oscillopsia during head movements ( Brandt, 1996 ). BVF has

wide spectrum of etiologies ( Zingler et al., 2007 ). The most common

ause of BVF is vestibulotoxicity of ototoxic drugs (specifically amino-

lycosides). New technical improvements allowing precise and easy

ssessment of vestibular function by videooculography have shown

* Corresponding author.

E-mail address: [email protected] (C. Helmchen).

213-1582/ $ - see front matter c © 2014 The Authors. Published by Elsevier Inc. This is anicenses / by-nc-nd / 3.0 / ).

ttp://dx.doi.org/10.1016/j.nicl.2014.03.003

that BVF is much more common as previously believed but etiology of-

ten remains unknown, i.e., idiopathic BVF ( Machner et al., 2013 ). Clin-

ical signs and prognosis of BVF are different from those of unilateral

vestibular failure (UVF). Vestibular neuritis patients complain about

acute vertigo and show spontaneous nystagmus and lateropulsion in

the acute phase. They have a fairly good recovery although a third of

all patients do not show peripheral regeneration. This has partly been

attributed to cortical and subcortical mechanisms of compensation

which have been studied by various brain imaging techniques, using

PET ( Becker-Bense et al., 2013 ; Bense et al., 2004a ), voxel based mor-

phometry ( Helmchen et al., 2009 ; Helmchen et al., 2011 ; Zu Eulen-

burg et al., 2010 ) and functional imaging of resting-state connectivity

open access article under the CC BY-NC-ND license ( http: // creativecommons.org /

http://dx.doi.org/10.1016/j.nicl.2014.03.003http://www.sciencedirect.com/science/journal/22131582http://www.elsevier.com/locate/yniclhttp://creativecommons.org/licenses/by-nc-nd/3.0/mailto:[email protected]://creativecommons.org/licenses/by-nc-nd/3.0/http://dx.doi.org/10.1016/j.nicl.2014.03.003http://crossmark.crossref.org/dialog/?doi=10.1016/j.nicl.2014.03.003&domain=pdf

M. G öttlich et al. / NeuroImage: Clinical 4 (2014) 488–499 489

( Helmchen et al., 2013 ).

The characteristic symptoms of BVF patients, oscillopsia and

blurred vision during head movements and locomotion, result from

a deficient vestibulo-ocular reflex (VOR) which normally stabilizes

gaze during rapid head movements. Gait unsteadiness in BVF is often

not attributed to a deficient VOR and therefore misdiagnosed. Unfor-

tunately, about 80% of BVF patients do not recover which may be due

to brain mechanisms which are entirely different from UVF ( Dieterich

and Brandt, 2008a ). While partial or complete peripheral vestibular

nerve regeneration ( Palla and Straumann, 2004 ; Schmid-Priscoveanu

et al., 2001 ) and central, presumably compensatory, mechanisms con-

tribute to vestibular rehabilitation in vestibular neuritis ( Alessandrini

et al., 2009 ; Becker-Bense et al., 2013 ; Bense et al., 2004a ; Helmchen et

al., 2009 ; Helmchen et al., 2013 ; Zu Eulenburg et al., 2010 ) peripheral

nerve dysfunction and dizziness in BVF are often permanent ( Zingler

et al., 2008 ). As the contralesional vestibular input subserving corti-

cal vestibular processing is missing, other non-vestibular mechanisms

have been suggested to provide central vestibular compensation in

BVF, e.g., substitution by changing the gain in the somatosensory

( Strupp et al., 1998 ) or visual system ( Dieterich et al., 2007a ). Re-

cently, a possibly adaptive mechanism of enhanced proprioceptive

signal interaction with cortical visual processing has been found in

BVF patients presumably subserving proprioceptive substitution of

vestibular function ( Cutfield et al., 2014 ).

In a recent meta-analysis considering 28 PET and fMRI studies

employing vestibular stimuli to healthy subjects Zu Eulenburg et

al. (2012) suggested the cytoarchitectonic area OP2 ( Eickhoff et al.,

2005 ) in the parietal operculum as the primary candidate for the

human vestibular cortex. In patients with BVF, PET brain imaging

(H 2 15 O) during vestibular caloric stimulation revealed decreased bi-

lateral activation in the “parieto-insular vestibular cortex” (PIVC)

compared to healthy controls ( Bense et al., 2004b ). Intersensory

cortical processing, specifically reciprocal cortical inhibitory visual–

vestibular interaction seemed to be preserved, though at reduced

levels, i.e., bilateral deactivation of the visual cortex, which is nor-

mally encountered during vestibular stimulation in healthy subjects,

was reduced and the posterior insula was less activated bilaterally

in BVF patients ( Bense et al., 2004b ). These data are based on be-

havioral or event-related brain activation studies. Changes in event-

related activation studies can be ambiguous as they may not reflect

the underlying pathophysiological mechanisms but only their be-

havioral consequences. In contrast, looking at the brain’s activity at

rest (resting-state) might shed more light on fundamental changes of

functional connectivity in the brain. Due to the lack of task demands,

resting-state fMRI (RS-fMRI) does not require an experimental de-

sign, patient’s compliance, and training, making it attractive in a clin-

ical environment. However, none of the previous studies looked at

resting-state brain activity in BVF patients using fMRI.

Recently, using RS-fMRI, we have shown decreased functional con-

nectivity in the intraparietal sulcus and supramarginal gyrus of pa-

tients with unilateral vestibular neuritis which partially reversed over

a period of three months when patients had improved. Interestingly,

this increase tended to be larger in patients with only little disability

in the follow-up examination suggesting a role in vestibular compen-

sation ( Helmchen et al., 2013 ).

In this study we examined brain intrinsic functional connectivity

in patients with bilateral vestibular failure (BVF). We used a novel

data driven approach based on graph theory to investigate altered

whole brain intrinsic functional connectivity in BVF patients as com-

pared to healthy controls. The so-called degree centrality ( Bullmore

and Sporns, 2009 ) served as a marker for altered connectivity. In

graph theory, the degree of a vertex (node) is defined as the number

of links (edges) connected to the node. The degree is thus a mea-

sure for the connectedness of a node within a network. Here, voxels

serve as nodes and edges are defined by the functional connectivity

between voxels. In contrast to network analyses which depend on

a given parcellation of the brain, this approach has a higher spatial

resolution and is not biased by a priori defined anatomical structures.

In previous studies, voxel-based network analyses were performed

to investigate topological properties of the brain network ( van den

Heuvel et al., 2008 ) and to identify network hubs, i.e., brain regions

which show a strong connectivity to the rest of the brain ( Buckner

et al., 2009 ; Zuo et al., 2012 ). Recently, the voxel-degree method was

successfully used as a marker for altered resting state functional con-

nectivity in Alzheimer’s disease ( Buckner et al., 2009 ), Parkinson’s

disease ( G ̈ottlich et al., 2013 ), and Obsessive Compulsive Disorder

( Beucke et al., 2013 ).

The aim of our study on BVF patients was therefore to elucidate

(i) whether there are changes in functional connectivity in brain ar-

eas involved in processing of vestibular information and (ii) whether

these changes during resting-state are related to subjective or ob-

jective parameters of vestibular impairment. Specifically, we chose

the deficient gain of the VOR which can be improved in a behavioral

context: UVF patients increase their VOR gain during self-guided, ac-

tive and thereby predictive head impulse movements as compared to

non-predictive, passive head impulses ( Black et al., 2005 ; Sprenger et

al., 2006 ). We hypothesized that BVF patients are also capable of us-

ing non-vestibular predictive mechanisms to stabilize images of the

visual world on the fovea. Therefore we compared functional connec-

tivity within neural networks in BVF patients with age- and gender

matched healthy controls and related the differences in this (active

vs. passive) vestibulo-ocular behavior to changes in functional con-

nectivity.

2. Materials and methods

2.1. Participants

Patients with bilateral vestibular failure (BVF) were compared

with age and gender matched healthy control subjects. The study

was approved by the institutional ethics committee of the University

of L ̈ubeck. All participants gave written informed consent before their

inclusion into the study. The study was performed in agreement with

the Declaration of Helsinki. Participants were recruited from an out-

patient neurology clinic in a tertiary care academic medical center at

the University of L ̈ubeck (Dizziness Center in L ̈ubeck, Germany). Pa-

tients complained about dizziness, gait unsteadiness and oscillopsia

during locomotion and head movements. All participants were right-

handed and underwent extensive neurologic, neuro-ophthalmologic,

and neuro-otologic examinations. BVF patients were on no regular

medication known to affect central nervous system processing. None

of the patients took any antivertiginous medication during the ex-

amination day. Patients were diagnosed to have BVF based on clini-

cal examinations by experienced neurologists and neuro-otologist of

the University Dizziness Center in L ̈ubeck and electrophysiological

recordings [bithermal cold (27 ◦) and warm (44 ◦) caloric irrigation,quantitative head impulse test] were analyzed by a co-worker with

longstanding experience in assessing vestibular function by caloric

and quantitative head impulse videooculography who did not know

about the history and clinical findings of the patients. Inclusion cri-

teria for BVF were the following: (1) clinical assessment of a bilater-

ally pathologic HIT ( Jorns-Haderli et al., 2007 ), (2) bilaterally reduced

gain of the horizontal VOR ( < 0.72) assessed by video-HIT ( Machneret al., 2013 ) (3) bilateral caloric hyporesponsiveness (mean peak slow

phase velocity (SPV) of < 5 ◦/ s on both sides), and (4) cranial magneticresonance imaging without structural brain lesions. Patients with de-

pression (as assessed by the Beck depression score) and dementia

(assessed by the MOCA scale) and those with additional evidence of

autoimmune and paraneoplastic diseases were excluded from the

study. Participants subjectively rated their level of disease-related im-

pairment by the Vertigo Handicap Questionnaire (VHQ) ( Tschan et al.,

490 M. G öttlich et al. / NeuroImage: Clinical 4 (2014) 488–499

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010 ), the Vertigo Symptom Scale (VSS) ( Tschan et al., 2008 ), the Clin-

cal Vestibular Score (CVS) ( Helmchen et al., 2009 ), and the Subjective

izziness Score (SDS) ( Helmchen et al., 2009 ). A total number of 33

atients with chronic ( > 3 months, range: 3 months to 20 years) BVF ere examined. 11 patients had to be excluded for various reasons:

xtensive head motion during MRI recordings ( n = 6), comorbidity n = 3) and brain lesions on MRI examinations ( n = 2). This resulted n 22 eligible BVF patients (12 males; age: 65.6 ± 9.8 years; disease uration: range 3 months to 20 years). The most common etiology of

VF was antibiotic ototoxicity ( n = 13; 59%), followed by idiopathic VF ( n = 4; 18%), sequential vestibular neuritis ( n = 2; 9%), cerebellar taxia with BVF ( n = 2; 9%) and Meniere’s disease ( n = 1; 5%). Thirty ealthy control subjects were recruited. All participants had normal

tructural MR images showing no signs of cerebral atrophy. Three

ontrol subjects were excluded due to extensive head motion and

wo subjects due to neuropsychiatric symptoms. Twenty-five healthy

ontrol subjects (14 males; age: 65.0 ± 9.2 years) were included in he study. The patient and the control group did not differ signifi-

antly in age (two-sample t -test p = 0.81; degrees of freedom: 45) or ender (chi-square test p = 0.71).

All participants were examined by a battery of vestibular investi-

ations. Semicircular canal function was investigated by electronys-

agmography with caloric irrigation and quantitative head impulse

est (qHIT) and otolith function by static (background stationary) and

ynamic (moving visual background) subjective visual vertical (SVV)

Dieterich and Brandt, 1993 ) and vestibular evoked myogenic poten-

ials (VEMPs). Psychophysical perception of the visual vertical was

ssessed by the subject’s adjustment of a bar to the perceived visual

ertical without any spatial orientation clues in a dotted hemispher-

cal dome, which is stationary or moving around the line of sight

Dieterich and Brandt, 1993 ). The normal range of SVV was defined as

eviation of < 2.5 ◦. Several but not all patients and all healthy partici- ants were investigated by ocular and cervical vestibular evoked myo-

enic potentials (oVEMP, cVEMP) ( Curthoys et al., 2012 ; Rosengren

nd Kingma, 2013 ). We used a vibration stimulus at the mid-forehead

elivered by a minishaker (Br ̈uel & Kjaer, Denmark) to elicit oVEMPs

ecorded from surface EMG electrodes beneath the lower orbital rim

bove the obliquus inferior muscle. To activate this muscle subjects

xated a target above their forehead. oVEMP was taken at a latency

f about 10 ms from the stimulus-locked ocular vestibular-evoked

yogenic potential and the first negative component. Cervical VEMPs

ere delivered by short tone bursts of 500 Hz to either ear (head-

hone) and recorded over tensed sternocleidomastoid (SCM) muscles

ilaterally. This results in a stimulus-locked short-latency myogenic

otential recorded (cVEMP) with an initial positive (inhibitory) po-

ential (p13) followed by a negative potential (n23) ( Rosengren et al.,

010 ).

.2. Quantitative head impulse test

All participants were examined by quantitative head impulse

est (qHIT) using video-oculography. Eye and head movements were

ecorded by the EyeSeeCam ® HIT System (Autronics, Hamburg, Ger-

any) at a sampling rate of 220 Hz. VOR gain was determined by ro-

ust linear regression of eye and head velocity starting at head veloc-

ty > 10 ◦/ s to 95% of peak head velocity using Matlab ®. Quantitative IT was delivered by passive head impulses (HIT) with rapid small

mplitude (10–15 ◦) horizontal head rotations (3000–4500 ◦/ s 2 ) while he participant was sitting on a chair fixating a red LED at a distance

f 100 cm. Quantitative horizontal HIT was performed under the fol-

owing conditions: Head impulses were either (i) passively conducted

eing unpredictable for direction and onset (inter-pulse interval: 4–

s, passive condition) ( Sprenger et al., 2006 ) or (ii) self-generated, i.e.,

ctively performed (participant driven). Prior to the second condition

active HIT), participants learned to make active head-impulses in

he same manner and velocity range as during passive head-impulses

while staring at the LED. The investigator monitored peak head ve-

locity during the active condition. We investigated if the VOR gain

difference under active (participant driven) and passive (investigator

driven) conditions is related to changes in functional connectivity.

2.3. Experimental design

The functional MRI data was acquired during a so-called resting-

state block of 6 minute duration. Subjects were instructed not to en-

gage in any particular cognitive or motor activity and to keep their

eyes closed.

2.4. Image acquisition

Structural and functional MRI images were recorded on a Philips

Achieva 3-T scanner (Philips Healthcare, the Netherlands). A total of

N = 178 functional images were acquired using a T2*-weighted single- shot gradient-echo echo-planar imaging (EPI) sequence sensitive to

blood oxygen level dependent (BOLD) contrast using the following

parameters: repetition time TR = 2000 ms; echo time TE = 30 ms; isotropic 3 mm voxel size; field of view 192 mm; 34 slices; 0.75 mm

interslice gap and flip angle 80 ◦. The slices were recorded in ascending interleaved order starting with odd slices. A standard 8-channel phase

array head coil was used. High resolution structural images were

obtained applying a T1-weighted 3D turbo gradient-echo sequence

with SENSE (image matrix 240 × 240; 180 slices; 1 × 1 × 1 mm 3 spatial resolution).

2.5. Preprocessing

Preprocessing was performed using the SPM8 software pack-

age (University College, London, Wellcome Trust Centre for Neu-

roimaging, http: // www.fil.ion.ucl.ac.uk / spm / ). The first 10 images of each dataset were discarded to allow for magnetization equilibrium

and for the subjects to adjust to the environment. The preprocessing

included the following steps: (i) Correction for differences in the im-

age acquisition time between slices; (ii) a six parameter rigid body

spatial transformation to correct for head motion during data ac-

quisition; (iii) co-registration of the structural image to the mean

functional image; (iv) gray and white matter segmentation, bias cor-

rection and spatial normalization of the structural image to a standard

template (Montreal Neurological Institute); (v) in order to reduce the

influence of motion and unspecific physiological effects, a regression

of nuisance variables from the data was performed. Nuisance vari-

ables included white matter and ventricular signals and the six mo-

tion parameters determined in the realignment procedure; (vi) spa-

tial normalization of the functional images using the normalization

parameters estimated in the previous preprocessing step and resam-

pling to 3 × 3 × 3 mm 3 ; (vii) spatial smoothing with a 6 mm full width half maximum Gaussian kernel; and (viii) a temporal bandpass

filter was applied to all voxel time series (0.01 Hz < f < 0.08 Hz). The six realignment parameters, i.e., three displacements and

three elementary rotations with respect to the first image in the EPI

series, were used as an estimator for the head motion. The displace-

ments with respect to the first image of the series were required to

be smaller than 3.0 mm (minimum to maximum) and the individ-

ual rotations smaller than 3.0 ◦. Subjects showing any displacement or rotation greater than these cut-offs were excluded.

2.6. Voxel degree maps

Voxel degree maps were calculated by correlating the temporal

BOLD signal fluctuation of each voxel with all other voxels in the brain and counting the number of connections above a certain threshold.

As a measure for the temporal correlation, we computed the zero-lag Pearson’s linear correlation coefficient r . The individual correlation

http://www.fil.ion.ucl.ac.uk/spm/


coefficients were entered into an N × N adjacency matrix where Nis the number of voxels. The voxel network matrix was thresholdedby r > 0.25 suppressing random correlations. This results in a binaryundirected network matrix d ij . The voxel degree D i was derived from

the network matrix as follows:

D i = N ∑

j = 1 d ij .

The degree maps were z-transformed to allow for averaging and

between subject comparisons:

z i = D i − D σD

( i = 1 . . . N ) .

Here, D denotes the mean degree and σ D the standard deviation.

2.7. Seed-based functional connectivity

Seed-based connectivity analyses were performed to investigate

the functional connectivity of a brain region of interest to the whole

brain ( Biswal et al., 1995 ; Vincent et al., 2006 ). The time courses of all

voxels within a sphere of 6 mm radius around the center coordinate of

a particular ROI were averaged and connectivity maps were calculated

by correlating the mean time course to all voxel time courses within

a brain mask. Correlations were computed using the Pearson product

moment formula. A Fisher z-transform was applied to all correlation

maps prior to the statistical analysis. A two-sample t -test was carried

out to identify regions of altered connectivity.

2.8. Statistical analysis

Differences in the voxel degree between healthy controls and

patients were investigated by a random effects analysis applying a

two-sample t -test. Statistical images were assessed for cluster-wise

significance using a cluster-defining threshold of p = 0.005. A topo-logical false discovery rate (FDR) procedure was used to correct for

multiple comparisons ( Chumbley et al., 2010 ; Chumbley and Friston,

2009 ). The FDR-corrected critical cluster size was k = 74. Voxel-wiseregression analyses were used to relate changes in regional connec-

tivity with behavioral data. The analysis was performed using SPM8

( http: // www.fil.ion.ucl.ac.uk / spm / ). The statistical analysis of behav-ioral data was performed using Matlab ®. If not stated otherwise we

report the mean and standard deviation of the data.

3. Results

3.1. Behavioral data

The mean VOR gain was larger for the active compared to the pas-

sive HIT. The increase of VOR gain during active HIT (gain: 0.46 ± 0.24;T (21) = 4.77; p < 0.0001; Fig. 1 C) was almost twofold as high com-pared to the passive HIT (VOR gain: 0.26 ± 0.18). An example of thisVOR gain difference is shown in Fig. 1 with original eye and head

velocity traces of passive (A) and active (B) head impulse test for a

single patient.

oVEMPs were recorded in 22 patients and 23 healthy control sub-

jects; they were absent in 12 patients and revealed reduced ampli-

tudes in the other 10 patients: peak amplitude differed significantly

between groups (Mann–Whitney U -Test p = 0.003, median patients:3.8 μV, median healthy control subjects: 6.95 μV). cVEMPs wererecorded in 22 patients and 23 healthy control subjects (median:

24.4 μV); they were absent in 17 patients and showed significantly re-duced amplitudes in the other 5 patients (median 8.0 μV; p = 0.028).There was no correlation between oVEMP peak amplitudes and z-

degree values of the cerebellum and posterior insula / parietal oper-culum (non-parametric Spearman-Rho correlation p always > 0.24);

the same holds for cVEMPs ( p always > 0.19). SVV did not show patho-logic tilts ( > 2.5 ◦) and did not differ between patients and controls,neither dynamic nor static SVV.

The Clinical Vestibular Score (CVS) revealed on average 10.2 ± 4.3.Subjective visual vertical in BVF patients was not different from con-

trols (patients: 0.2 ◦ ± 2.6 ◦; controls: 0.6 ◦ ± 1.2 ◦; two-sample t -test p = 0.61). Subjective disease-related impairment for the VertigoHandicap Questionnaire (VHQ) revealed on average 30.1 ± 19.1, forthe Vertigo Symptom Scale (VSS) on average 35.0 ± 22.7 and the Sub-jective Dizziness Score (SDS) on average 13.1 ± 8.4. SDS was highlycorrelated ( r > 0.6; p < 0.01) with the CVS, VHQ and VSS. There wasno correlation of any of these scores to disease duration.

3.2. Altered intrinsic functional connectivity

Between-group differences in the voxel-degree obtained in the

random effects analysis are summarized in Fig. 2 and Table 1 . Pa-

tients showed lower functional connectivity of the posterior insula

and parietal operculum bilaterally (CTR > BVF in Fig. 2A ; Table 1 A)and a higher connectivity in the cerebellum (BVF > CTR in Fig. 2B ;Table 1 B). The anatomical assignment was derived from the location

of local cluster maxima, i.e., brain regions where we observed the

strongest between-group effects.

We used cytoarchitectonic probability maps of the parietal oper-

culum (SII) and the insular cortex from the SPM Anatomy toolbox

( Eickhoff et al., 2005 ) to specify the anatomical location of our find-

ings. 12% of the left cluster overlapped with the insular gyrus II (cov-

ering 39% of this region) and 8% with the parietal operculum areaOP4

(covering 7%). For the right cluster we found an overlap of 4% with

the parietal operculum area OP4 (covering 4%) and of 3% with area

OP3 (covering 6%). The remaining voxels (80% for the left hemisphere

and 93% for the right hemisphere) comprising the cluster were lo-

cated in the superior temporal gyrus and more anterior regions of the

operculum.

Applying cytoarchitectonic probability maps of the cerebellum

( Eickhoff et al., 2005 ), we found that 36% of the cluster in the left

cerebellar hemisphere is assigned to the left lobule VIIa Crus II. 17%

of the cluster in the right cerebellar hemisphere is located in the lob-

ule VIIa Crus I and 16% in the lobule VI. The remaining voxels are

distributed over other regions of the cerebellum. We only quote cere-

bellar regions where we found more than 10% of the voxels.

We repeated the analysis excluding the two patients with cere-

bellar ataxia and identified the same clusters (left hemisphere: ad-

justed p -value 0.036, cluster maximum −27 −72 −42 mm; right hemi-sphere: adjusted p -value 0.036, cluster maximum 30 −48 −39 mm).Therefore we conclude that our results are not driven by the BVF

patients with cerebellar signs.

The mean degree in the clusters in which we found significant

degree differences between BVF patients and healthy controls did not

correlate with the disease duration (Pearson’s linear correlation; all

p > 0.1).

3.3. Investigation of underlying network changes

We performed seed-based functional connectivity analyses inves-

tigating four seed regions located in the posterior insula. Note that we

followed a purely descriptive approach to gain a deeper understand-

ing of the underlying network changes indicated by the differences in

the voxel-degree. Fisher z-transformed functional connectivity maps

for the control (CTR) and the patient (BVF) group are shown in Fig. 3 A.

The spherical seed region with a radius of 6 mm was placed in the right

posterior insula (MNI coordinates of ROI center 42 −9 3 mm). Fig. 3Ashows the between-group effects in functional connectivity accord-

ing to a two-sample t -test. As a cut-off for the descriptive analysis of

the between group effects a cluster defining threshold of p = 0.001

http://www.fil.ion.ucl.ac.uk/spm/


Fig. 1. Quantitative head thrust test. Eye and head velocity traces of the passive (A) and active (B) head impulse test of a single BVF patient are shown. (C) Vestibulo-ocular reflex

(VOR) gain (mean ± standard error) of all BVF patients was significantly larger during active as compared to non-predictive passive head impulses (paired t -test; p = 0.0001).

Table 1

Between-group differences (BVF patients vs. healthy controls) in degree centrality.

Anatomical region

p (adj.)

(cluster) k Local maxima [mm]

T

(peak)

x y z

A) CTR > BVF

Posterior insula R 0.003 132 33 −3 −9 4.62 Parietal

operculum

R 48 0 6 4.48

Posterior insula R 42 −9 3 3.70 Posterior insula L 0.002 161 −48 −9 6 4.36 Parietal

operculum

L −36 −15 6 4.17

Superior

temporal gyrus

L −54 −3 −12 4.02

B) BVF > CTR

Cerebellum R 0.043 79 −15 −72 −39 4.10 −27 −72 −42 4.07 −9 −69 −33 3.54

Cerebellum L 0.019 108 27 −48 −39 4.00 21 −66 −42 3.85 30 −66 −39 3.58

Notes: Clusters with differences in the voxel degree between patients and controls (cluster defining threshold p < 0.005; topological FDR-correction). Anatomical region, adjusted

cluster level probability and number of voxels per cluster ( k ) are listed. The table shows 3 local maxima (MNI coordinates) more than 8.0 mm apart and the peak T -scores.

a

n

s

f

o

(

e

s

t

r

l

r

(

3

(

t

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3

i

nd a cluster size of k > 50 were chosen. We tested for higher con- ectivity in the control group with respect to patients (CTR > BVF) as uggested by the higher degree of connectivity in the posterior insula

ound in the control group. Controls showed a stronger connectivity

f the posterior insula (right) to the anterior insula (left), precuneus

right), cingulate cortex and the inferior / middle frontal gyrus (bilat- ral) ( Table 2 ). We applied the same analysis approach to three other

eed regions in the posterior insula ( Fig. 3B ). Each color represents

he pattern of significantly altered connectivity for an individual seed

egion (cluster defining threshold p = 0.001; cluster size k > 50). The ocations (MNI coordinates) of the four seed regions ( Fig. 3B ; on the

ight) had the following MNI coordinates: 1) ROI center 42 −9 3 mm red); 2) ROI center −36 −15 6 mm ( Rerkpattanapipat et al., 2009 ); ) ROI center −48 −9 6 mm (green); and 4) ROI center 48 0 6 mm yellow).

We repeated the seed-based connectivity analysis by decreasing

he radius of the spherical seed regions to r = 4 mm and found that his did not affect our results.

.4. Relationship to the VOR gain improvement

We performed a whole brain voxel-wise regression analysis to

nvestigate if the degree centrality is modulated by the VOR gain

difference (active minus passive). There was a striking positive cor-

relation of this context-dependent VOR gain difference (active mi-

nus passive non-predictive VOR) to the degree centrality in the

right supramarginal gyrus ( Fig. 4 A; Table 3 ), cerebellum, and straight

gyrus ( Fig. 4 A; topological FDR correction; cluster defining threshold

p = 0.005; 0.05 FDR-corrected cluster size was k = 74). These brain regions showed a stronger connectivity to the rest of the brain the

larger the VOR gain was increased in the active HIT, i.e., connectiv-

ity increased as the difference between active and passive predictive

VOR gain became larger. The cluster in the SMG contained 88 voxels.

Thirty-eight percent of the voxels overlapped with the cytoarchitec-

tonic region PFm of the supramarginal gyrus ( Caspers et al., 2006 )

(covering 13% of this region) and 17% with the PFcm region (covering

16%). Applying cytoarchitectonic probability maps of the cerebellum

( Diedrichsen et al., 2009 ; Eickhoff et al., 2005 ), we found that 49% of

the cluster in the cerebellum is assigned to the lobule VIIa Crus I and

46% to the lobule VIIa Crus II.

For all subjects we extracted the mean z-degree in two clusters

(SMG and cerebellum) where we observed a significant correlation

between the functional connectivity (z-degree) and the VOR gain dif-

ference. Fig. 4 B shows the interrelation between the mean z-degree

and the VOR gain difference (active–passive) for BVF patients.

In an exploratory approach, we tested if the degree centrality is

correlated to the VHQ or the VSS. There was no correlation between


Table 2

Functional connectivity of the right posterior insular cortex in healthy controls compared to BVF patients as depicted in Fig. 3A .

Anatomical region k T (peak) Local maxima [mm]

x y z

Inferior / middle frontal

gyrus (left)

228 4.34 −42 30 15

4.13 −33 36 39 4.06 −42 12 9

Inferior / middle frontal

gyrus (right)

108 4.97 45 27 21

3.62 30 33 33

Dorsal anterior cingulate

cortex

96 4.63 6 3 30

3.95 −3 6 27 3.94 0 15 27

Precuneus (right) 56 4.38 9 −60 51 4.07 3 −69 51

Notes: the table shows 3 local maxima (MNI coordinates) more than 8.0 mm apart, the cluster size k and the peak T -scores. Note that this is the results of a descriptive analysis

investigating the higher connectivity observed in the posterior insula.

Table 3

Correlation between VOR gain difference (active–passive VOR) and the voxel-degree (differences BVF patients vs. controls).

Anatomical region

p (adj.)

(cluster) k Local maxima [mm]

T

(peak)

x y z

Cerebellum (right) 0.013 114 21 −84 −45 5.28 21 −81 −30 4.88 24 −75 −36 4.18

Supramarginal

gyrus (right)

0.027 88 45 −45 33 4.70

45 −33 30 4.33 51 −42 27 4.29

Gyrus rectus 0.040 74 −3 42 −24 4.87 15 33 −27 4.32 18 24 −27 3.72

Notes: Clusters showing a positive correlation of the z-degree to the VOR gain difference (cluster defining threshold p < 0.005; topological FDR-correction; FDR-corrected critical

cluster size was k = 74). Anatomical region, adjusted cluster level probability and number of voxels per cluster ( k ) are listed. The table shows 3 local maxima (MNI coordinates) more than 8.0 mm apart and the peak T -scores.

the degree centrality and these disease-related disability scores. Note,

that the two scores are strongly correlated (Pearson’s linear correla-

tion coefficient r = 0.6; p = 0.029), i.e., not statistically independent.

4. Discussion

In contrast to previous brain imaging studies on vestibular dis-

ease, which largely used stimulus-related fMRI or PET designs, we

used a data driven approach to investigate whole-brain resting-state

functional connectivity in patients with chronic bilateral vestibular

failure (BVF) compared to healthy controls. Most network analyses

depend on a given parcellation of the brain, e.g., brain regions based

on the SPM AAL template ( Tzourio-Mazoyer et al., 2002 ). However,

our voxel-based approach is not biased by an a priori hypothesis

confined to defined anatomical structures and has a higher spatial

resolution.

As a main result we found reduced functional connectivity of the

posterior insula, parietal operculum and the superior temporal gyrus

compared to healthy control subjects. These areas belong to vestibu-

lar cortex regions integrating multisensory signals into a percept of

spatial orientation and self-motion. Importantly, these changes were

found in BVF patients at rest, i.e., without any vestibular stimulation,

which indicates a much more fundamental disease-related change

in the resting brain: a change of resting-state connectivity. This re-

duced connectivity may be related to the poor prognosis of vestibu-

lar rehabilitation in BVF. Interestingly, however, one feasible clini-

cal implication comes from the improvement of context-dependent,

i.e., self-guided vestibular behavior with increasing connectivity in

vestibular cortical areas (supramarginal gyrus, inferior parietal lobe)

of BVF patients.

4.1. Functional connectivity of the posterior insula and the parietal

operculum

We found reduced functional connectivity in the posterior insula,

superior temporal gyrus and the parietal operculum. Pioneer animal

work identified vestibular responses in the parieto-insular vestibu-

lar cortex (PIVC) in the posterior insula of the monkey ( Grusser et

al., 1990 ; Guldin and Grusser, 1998 ). Additional vestibular responses

were found in animal experiments in adjacent retroinsular areas, the

ventral intraparietal area in the fundus of the intraparietal sulcus

( Bremmer et al., 2002 ). These regions showed increased neural activ-

ity (fMRI) during various vestibular (e.g., caloric, galvanic) stimuli in

healthy human subjects. Specifically the middle and posterior insula,

inferior parietal cortex, and posterior parietal cortex belong to mul-

tisensory cortical areas processing vestibular information ( Becker-

Bense et al., 2013 ; Bense et al., 2001 ; Dieterich et al., 2003 ; Emri et al.,

2003 ; Fasold et al., 2002 ; Lobel et al., 1998 ; Lopez and Blanke, 2011 ;

Naito et al., 2003 ; Seemungal et al., 2009 ; Stephan et al., 2005 ; Suzuki

et al., 2001 ). Electrical stimulation in a lateral temporo-parietal area

in humans elicited rotatory sensations ( Kahane et al., 2003 ). STG and

IPL also revealed structural changes in gray matter volume in unilat-

eral vestibular failure patients ( Helmchen et al., 2009 ; Helmchen et

al., 2011 ).

In a PET study on BVF patients, task-independent metabolism


Fig. 2. Between-group effects in resting-state connectivity (expressed by the degree

centrality). Statistical images were assessed for cluster-wise significance using a cluster

defining threshold of p = 0.005 applying a topological q = 0.05 FDR-correction. Regions with increases in connectivity (as indicated by a larger degree centrality) in healthy

controls (CTR) compared to patients (BVF) are shown in (A); regions with a larger

connectivity in patients compared to controls in (B).

w

t

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as strongly reduced in posterior insula ( Bense et al., 2004b ). Pa-

ients with bilateral vestibular hypofunction need to engage other

ensory systems to compensate for deficient gaze stability, gait con-

rol, self-motion perception and spatial orientation. For this reason

ot only vestibular but also other sensory (visual, somatosensory)

timuli have been used to investigate the brain’s responses to pe-

ipheral vestibular failure. Neural activity of cortical reciprocal in-

ibitory visual–vestibular interaction was changed: neural activity

n the posterior insula and parietal operculum was decreased during

aloric vestibular stimulation and concurrent deactivations in the vi-

ual cortex were absent or reduced in BVF ( Bense et al., 2004b ). In

he same region (posterior insula) and the parietal operculum as well

s superior temporal gyrus we found decreased bilateral functional

onnectivity compared to healthy controls. This reduction may affect

eciprocal inhibitory visual–vestibular interaction which is normally

equired for spatial orientation and motion perception. On a behav-

oral level, distressing oscillopsia in BVF patients can be reduced by

hanging the cortical sensitivity of motion perception ( Grunbauer et

l., 1998 ; Kalla et al., 2011 ). Using a motion coherence paradigm, BVF

atients showed raised thresholds of motion detection ( Kalla et al.,

011 ). This has been taken as an adaptive process to compensate

or oscillopsia. On the other hand, activations of the primary visual

ortex and motion-sensitive areas V5 in the middle and inferior tem-

oral gyri during optokinetic stimulation were significantly larger

han those of age-matched healthy controls ( Dieterich et al., 2007b ).

n upregulation of the visual sensitivity has been suggested and in-

erpreted as a substitutional mechanism to compensate for deficient

estibular function. Our analysis did not show changes of connectiv-

ty in the visual cortex as a potential cause for altered responsiveness

o visual motion.

The core vestibular region, OP2, primarily processes vestibular in-

formation but does not necessarily represent a multisensory area ( Zu

Eulenburg et al., 2012 ). In contrast, the posterior insula responds to

multisensory stimulation ( Zu Eulenburg et al., 2013 ). Thus, one rea-

son for decreased cortical responses to vestibular stimulation in BVF

patients ( Bense et al., 2004b ) may be reduced connectivity in OP2

and neighboring posterior insular areas at rest. It remains open at

present whether this is a consequence of long lasting cortical depri-

vation from vestibular stimuli in BVF or whether this constitutes a

secondary mechanism related to the poor vestibular rehabilitation in

these patients.

4.2. Reduced connectivity of posterior insula: targets and physiological

role

To gain a deeper understanding of the underlying network changes

we investigated seed-based functional connectivity maps with seeds

in the posterior insula. Any seed-based functional connectivity anal-

yses in regions of degree differences are biased. It should be stressed

that we followed a purely data-driven descriptive approach to in-

vestigate which brain regions are involved in the observed degree

differences.

The seed-based analysis showed diminished connectivity from the

posterior insula of BVF patients to the middle frontal gyrus, ante-

rior cingulate cortex (ACC) and superior parietal lobule comprising

the precuneus ( Table 2 ). Apart from the posterior insula, the parietal

operculum and the superior temporal gyrus, the precuneus and the

ACC are repeatedly activated during vestibular stimulation ( Dieterich

and Brandt, 2008b ; Zu Eulenburg et al., 2012 ). Our data complements

and extends these findings by showing that the corresponding neu-

ral networks are affected which cannot be derived from the simple

observation of co-activation alone.

The dorsal anterior insula has cortical projections to brain regions

involved in executive functions and cognitive control ( Deen et al.,

2011 ), e.g., the anterior cingulate cortex (ACC) ( Dosenbach et al., 2007 )

which might help to monitor errors and mismatches resulting from

multisensory, i.e., somatosensory, interoceptive and vestibular infor-

mation from the posterior insula ( Corbetta et al., 1993 ). By detecting

a mismatch between expected and actual vestibular feedback or by

receiving contradicting information from different sensory systems,

the ACC may facilitate decision making processes to adapt behavior

and may mediate context-driven modulation of bodily arousal states

( Critchley et al., 2003 ). Although there is some human and animal

data supporting a role of ACC, specifically Brodmann area 24 in the

interface of motor control, arousal / drive state and cognition ( Paus, 2001 ), which makes ACC a potential candidate to translate intentions

to actions, data are required to show that this interface operates suffi-

ciently fast to modulate a vestibular driven motor behavior with such

a short latency as the vestibulo-ocular reflex.

The precuneus (Brodmann area 7) was shown to be activated dur-

ing caloric vestibular stimulation ( Dieterich et al., 2003 ; Dieterich and

Brandt, 2008b ). According to monkey data, area 7 showed structural

connections with subcortical regions involved in vestibulo-ocular

function ( Faugier-Grimaud and Ventre, 1989 ; Ventre and Faugier-

Grimaud, 1986 ). Thus there is some evidence for a role of the pre-

cuneus in the cortical vestibular circuit.

We conclude that our data suggests that enduring deficient or

missing vestibular input weakens the functional connectivity within

the vestibular cortical network.

As the threshold of our descriptive analysis is arbitrary, we re-

peated the seed based analysis by changing the p -threshold to

p = 0.005 and looked for consistent effects. For all four seed regions we found the hippocampus (left and right hemispheres) to

be consistently more connected to the posterior insula in the con-

trol group compared to patients. This extends previous observations

by Brandt and co-workers of structural changes of the hippocampus


Fig. 3. Seed-based functional connectivity analyses with seed regions located in the posterior insula. A) Fisher z-transformed functional connectivity maps for the control (CTR;

first row) and patient (BVF; second row) groups. The spherical seed region with a radius of 6 mm was located in the right posterior insula (MNI coordinates of ROI center 42 −9 3 mm). Between-group effects in functional connectivity (CTR > BVF) are shown in the third row. B) Between-group effects for four different seed regions in the posterior insula

are shown for the contrast CTR > BVF (red: ROI center 42 −9 3 mm; blue: ROI center −36 −15 6 mm; green: ROI center −48 −9 6 mm; yellow: ROI center 48 0 6 mm).

of BVF patients who also exhibited spatial memory and navigation

deficits ( Brandt et al., 2005 ). Our data provide additional pieces of

evidence for a neural correlate of impaired spatial orientation in BVF.

Furthermore, we selected different seed-regions in the parietal oper-

culum and posterior insula and showed that the connectivity patterns

for the different seed regions converge.

4.3. Increased cerebellar functional connectivity in BVF

Interestingly, our BVF patients showed a higher connectivity in

the cerebellum compared to healthy controls. The cerebellar region

Crus I showed functional resting state connectivity with the dorsolat-

eral prefrontal cortex, the inferior parietal lobule, pre-supplementary

motor area and the anterior cingulate cortex ( Buckner et al., 2011 ).

The cerebellar region at the border of Crus I / II is functionally con-nected with cerebral regions related to the default mode network

(posterior cingulate cortex, lateral temporal cortex, inferior parietal

lobule and medial prefrontal cortex) ( Buckner et al., 2011 ). Bernard et

al. (2012) found that the cerebellar region Crus I is functionally con-

nected to the superior frontal gyrus (frontal eye fields) and the angular

gyrus in the inferior parietal cortex which represents awareness that

an intended action is consistent with movement consequences and

the awareness of the authorship of the action ( Farrer et al., 2008 ).

It is intriguing to speculate that this increased cerebellar connectiv-

ity indicates compensatory substitutional processes to improve the

awareness of self-initiated movements or contributes to an improved

coordination between parietal and frontal eye fields. Some support

comes from the fact that functional connectivity in this cerebellar

region correlates with the degree by which self-guided (active) VOR

gets larger when compared with passive VOR (see below).

4.4. Relation of changes in functional connectivity and clinical

performance

Seventy percent of BVF patients do not show spontaneous im-

provement over time ( Zingler et al., 2008 ). Unlike UVF patients

( Helmchen et al., 2013 ), who usually recover, it is less promising

to relate clinical consecutive recordings in BVF to follow-up imag-

ing data. Therefore we related changes of functional connectivity to a

context-dependent vestibular behavior in BVF. By comparing the VOR

gain during active and passive head movements we found that BVF

patients can impressively increase their VOR gain if head-movements

are actively performed. Interestingly, functional connectivity in the

supramarginal gyrus, the rostro-dorsal part of the inferior parietal


Fig. 4. Interrelation between the connectivity (z-degree) and the VOR gain difference. A) Brain regions with a positive correlation between connectivity (z-degree) and context-

dependent (active–passive) VOR gain differences are shown (cluster defining threshold p < 0.005; topological FDR-correction; FDR-corrected critical cluster size was k = 74). B) Interrelation between the mean connectivity (z-degree) and the VOR gain difference (active–passive VOR gain) for BVF patients. The larger the differences between active vs.

passive VOR gain the larger the regional increase in connectivity in the supramarginal gyrus (upper panel) and cerebellum (lower panel). The mean z-degree was extracted from

the clusters in which there was a significant correlation between the z-degree and the VOR gain difference.


lobe, correlated with the context-dependent increase in the vestibulo-

ocular performance, i.e., the larger the increase of VOR gain difference

between active and passive head movements the larger was the in-

crease in functional connectivity in this region. In contrast, changes

of functional connectivity in these regions were not related to otolith

dysfunction.

The supramarginal gyrus (SMG) belongs to the inferior parietal

lobule which is a cortical multisensory integration area ( Zu Eulenburg

et al., 2012 ). In association with the superior temporal gyrus and the

posterior insula it receives and integrates visual, vestibular and so-

matosensory information to construct a coherent spatial orientation

( Angelaki and Cullen, 2008 ; Lopez and Blanke, 2011 ). This has been

corroborated by human cortical lesion studies ( Baier et al., 2012 ), elec-

trical stimulation studies ( Kahane et al., 2003 ) and functional imaging

studies ( Lopez et al., 2012 ). Its implication for vestibular processing

has been shown not only in event-related stimulation studies but also

at rest. We recently found decreased functional connectivity in SMG

and adjacent intraparietal sulcus in acute unilateral vestibular neuritis

patients which recovered over time as individual vestibular-induced

disability improved ( Helmchen et al., 2013 ). Additional evidence for

multisensory integration of the SMG comes from a recent transcranial

magnetic stimulation (TMS) study. TMS of the supramarginal gyrus

in healthy human subjects selectively elicited tilts of the subjective

visual vertical (SVV), a perceptional correlate of our static upright ref-

erence ( Kheradmand et al., 2013a ). It is generated by the integration

of vestibular, visual and proprioceptive signals which can be patho-

logically tilted by cortical lesions ( Brandt and Dieterich, 1994 ). This

supports a role of SMG in multisensory integration to establish an

accurate upright perception. The lateralization, i.e., the right-sided

increase in functional connectivity in our BVF patients with active

vs. passive head movements is compatible with the specialization of

the right human hemisphere in spatial orientation and its dominance

in vestibular processing ( Dieterich et al., 2003 ; Fink et al., 2003 ). A

common reference system for spatial orientation can only be derived

from a transformation of the different coordinate frames of the differ-

ent sensory systems. The SMG but not the posterior insula has been

shown to contribute to this internal reference of upright perception

(SVV) and spatial orientation ( Kheradmand et al., 2013b ). Moreover,

not only the SVV but also the VOR may become asymmetric by right-

sided cortical temporoparietal lesions in patients involving the SMG

( Ventre-Dominey et al., 2003 ).

The adjacent ventral intraparietal area (VIP) contains neural rep-

resentations of self-motion based on vestibular and visual signal inte-

gration ( Chen et al., 2011 ). It contains neurons that respond to head-

movement related signals in relation to passive and active movements

( Klam and Graf, 2003b ). The variety of neuronal responses ranging

from total extinction to activity only during active head movements

suggests a role of VIP in sensory space representation ( Klam and Graf,

2003a ). The posterior parietal cortex and the vestibular nuclei are

likely candidates to contribute to the distinction between active and

passive head movements since the peripheral vestibular receptors

cannot ( Roy and Cullen, 2004 ). Sensory space representation is influ-

enced by non- or extra-vestibular inputs such as motor efference copy

signals of the neck and head motor command and the proprioceptive

feedback signal. They allow to predict the gaze error and may substi-

tute for the bilateral loss of vestibular information to stabilize gaze

during head movements by, e.g. preprogramming compensatory eye

movements ( Della Santina et al., 2002 ) or by increasing the weight

of neck motor efference copy which can be sufficient to explain im-

provements in gaze stability during active self-motion ( Sadeghi et al.,

2012 ). The increased intrinsic connectivity with increasing VOR gain

during active head movements in BVF implies a functional role of the

SMG in the sensory substitution and integration of motor efference

copy signals.

Interestingly, the posterior cerebellum similarly showed increas-

ing functional connectivity with increasing VOR gain during active

head movements. Vestibular nucleus neurons encoding the differ-

ence between the expected reafference and the sensory consequence

of the actual movement project to the cerebellum which is probably

involved in anticipating VOR responses ( King, 2013 ). The cerebellar

role in anticipating sensory consequences of motor behavior is well

established ( Ploghaus et al., 1999 ) and one might speculate that in-

creased cerebellar functional connectivity in our BVF patients helped

to predict their own gaze error and to elicit a compensatory, stronger

eye velocity signal with active HIT. Intrinsic functional connectiv-

ity studies have recently demonstrated strong functional cerebello-

cerebral connectivity of the visual and sensorimotor network, specif-

ically from cerebellar lobule VI to the inferior parietal lobe ( Kipping

et al., 2013 ) and from cerebellar Crus I to the superior frontal gyrus

(frontal eye fields) and the angular and supramarginal gyrus ( Bernard

et al., 2012 ). A stronger connectivity to the frontal eye fields and the

SMG may facilitate better performance of gaze stabilization in the

passive HIT condition. Future connectivity studies will have to inves-

tigate whether this cerebello-cerebral functional connectivity to the

inferior parietal lobe can be modulated to improve vestibular reha-

bilitation in BVF.

5. Conclusions

Our study provides first evidence that there is a strong change

in resting-state activity even without vestibular stimulation indicat-

ing profound behavioral task-independent changes in resting-state

functional connectivity of BVF patients. Our data driven approach

revealed decreased functional connectivity of the posterior insula

(PI) and the parietal operculum (OP) in BVF patients. These regions

are multisensory regions processing somatosensory, nociceptive and

vestibular information which have been identified as core regions

of vestibular cortical processing in hypothesis-driven event-related

activation studies. These regions can now be used as seed regions

to identify the directions and targets of these altered connectivity

and their relation to levels of functional impairments in vestibular

disease.

Acknowledgments

This work was supported through intramural funding of the Uni-

versity of L ̈ubeck. UMK and TFM receive support from the DFG.

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